Development of Spatial Inspection Methods to Support Building Inspections and Compliance

Supervisor: Prof Bert Veenendaal, Robert Corner

In Riyadh, the capital city of Saudi Arabia, building inspections result in construction violations when approved building plans are changed and building regulations are disregarded. This research investigates how spatial information methods can be used to support and improve the local building inspection process.

The methods developed will support enforcement by building inspections of approved building plan compliance, building regulations and instructions using geographic information system (GIS) tools. The GIS tools will be used to develop a spatial inspection framework in the building inspection process. The building inspection framework must therefore be designed to support Saudi building process in order to manage compliance and maintain some conflict between the public and the planning department.

A case study will be used to explore, analyse and evaluate the integration and implementation of GIS tools in building inspections. This research will incorporate some fieldwork, including interviews and a review of existing records. The study will help building inspectors improve their knowledge of the building inspection task and to become familiar with spatial inspection methods in order to support and enforce approval building plan compliance within local government regulations.

Social Journey prototype for people with Autism Spectrum Disorder (ASD)

Supervisors: Dr David McMeekin, A/Prof Tele Tan

Ontology is used as an explicit specification of a conceptualization. In computer and information science, ontology is a technical term denoting an artefact that is designed for a purpose, which is to enable the modelling of knowledge about some domain. The Transport disruption ontology is a formal framework for modelling travel and transport related events that have a disruptive impact on travellers’ journeys. This research aims to provide a social journey prototype using the transport disruption ontology, social networks and language interpretation to assist people with Autism Spectrum Disorder (ASD) effectively plan and manage their travel.

The research will contain the development and piloting of what is needed in the construction of the prototype through the analysis of disruptive events presented in official reports and social networks, mapping those disruptions within any planned journey and evaluating their disruption to create a new on-the-fly journey and provide advice on alternate routes using communication methods suitable for people with ASD.

Huge amounts of data – including location information – are available online, with the volume increasing all the time. This makes finding relevant data increasingly diffcult: Where do you start looking? Who holds the data? How do they refer to it, and what happens if their terminology differs from language used by data seekers? This project uses online agents to solve specialist search tasks. Each agent builds upon known input and output formats which allows them to be coordinated to solve more complex tasks, such as finding themed spatial features within a named region. Results can include probabilities of the relevance of results, helping users judge which to use or investigate further. For example, ranking results by how well their descriptions match the meaning (semantics) of the query, or by spatial proximity to the user.

Current systems used to find spatial data are difficult to use and don’t always find the right results. Using general purpose systems such as Google, however, will not deliver the required results unless very specific terminology is used. Through the use of natural language processing of queries, more relevant results can be returned to the user by determining the precise area they wish to find data in as well as expanding the user’s query through a ‘thesaurus’. In the case of domain-specific terms, a thesaurus can be built from relevant non-structured data such as technical reports and spreadsheets.

The automatic federation of Australia’s spatial information is needed to improve access to up-to-date spatial data throughout the jurisdictions. Due to the ever increasing demand for better quality spatial information throughout the world, the spatial community is in need of more efficient and automated spatial information systems. Automatically federating Australia’s spatial information on-the-fly would solve a lot of current duplication, conflation, and data updates issues, but more importantly, by incorporating semantics in spatial information, it would lift the burden on users by removing the currently used mass downloading method and only provide the data the user wants, allowing for better geospatial based decisions. This research aims at finding ways and implementing a system to automatically consolidate multiple heterogeneous uncontrollable data sources in a semantic manner. The difficulties to be addressed include database interoperability, database heterogeneities, and use of adequate existing tools and concepts.

Current geospatial datasets and web services are disparate and difficult to expose. With the advent of geospatial processes utilizing temporal data and big data, the problem of under-exposed datasets and web services is amplified. End users are required to know the exact location of these online resources, their format and what they do.

In a typical example, to locate a Web Service that performs flood modelling, a Google Search for “Flood Modelling Web Service” is insufficient to find relevant results. This research proposes the integration of semantic web concepts and technologies into geospatial datasets and web services, making it possible to link these datasets and services via functionality, the inputs required and the outputs produced. To do so requires the extensive use of metadata to allow for a standardised form of description of their function. The use of ontologies and AI (Artificial Intelligence) then allows for the intelligent determination of which web services and datasets to use, and in what order they are to be used to achieve the desired final output.

This research aims to provide a method to automatically and intelligently chain together web services and datasets to assist in a geospatial analyst’s productivity.

ALCOA have been involved in bauxite exploration and mining within the Northern Jarrah Forest of Western Australia for over 30 years. Throughout this period ALCOA has committed to the on-going collection of spatially-enabled floristic plot, environmental and borehole geochemistry data to assist in forest monitoring and bauxite exploration operations. However, despite the potential of the data to assist ALCOA in enhancing exploration targeting through modern mineral prospectivity modelling, the data remains mostly unused. This project aims to utilise this extensive and spatially-enabled dataset for the first time to undertake mineral prospectivity modelling in the region. A spatial database will be developed to standardise, manage and expand the provided floristic and geochemistry dataset. A conceptual model of bauxite formation will be developed and all further identified formation factors will be sourced as spatial data, processed, and maintained within the database. Modelling will then be undertaken using data-driven and knowledge-driven approaches (e.g. Weights of Evidence and Fuzzy Membership theory) and will be validated using known bauxite deposits provided by ALCOA.

The Classification and use of Landform Information to increase the Accuracy of land Condition Monitoring in Western Australia Pastoral Rangelands

Supervisor: Robert Corner, Ashraf Dewan

This research involves an investigation into the classification and use of landform information in the pastoral rangelands in Western Australia (WA). The landform data will provide the Department of Agriculture and Food Western Australia (DAFWA) with information to increase accuracy and assist land condition monitoring projects such as Pastoral Lease Assessment using Geospatial Analysis (PLAGA), Western Australian Range Monitoring System (WARMS) and field surveys in pastoral rangelands. This research is unique as it will provide the capability to map landforms at a land subsystem level in areas where the land surface is currently only mapped at a land system level.

The importance of landform data at a land subsystem level is that it provides higher resolution and therefore greater detail to land surface mapping within the rangelands of WA. A probabilistic model such as Weights of Evidence (WofE) is suggested to extend these landform features into other pastoral rangeland areas. Ground-truth testing will be used to define uncertainties and contribute to geomorphology. Monitoring of the rangeland conditions in WA is vital for pastoral lease preservation and to encourage recovery.

In the GIS industry, the focus has now moved from solving single problems by using highly specific spatial data models to a more general data sharing model. Data sharing models can provide multiple spatial views, applications, and access points to different users by including enabling technologies such as networking, distributed computing and web technology in a spatial database system. In a spatial database, spatial views (an extension of the classical database views concept) provide flexible representations of the underlying database and are used to create a range of customized map products for end users.

Due to the ever-changing nature of the real world represented by a spatial data model, spatial database schema are often subject to changes during the database life cycle. Whilst schema evolution has always been an active research area, very few projects have been conducted on spatial databases. This is especially the case for federated spatial databases where multiple databases from different organizations are integrated to provide spatial data sharing. Spatial views in such an environment can be related to one or multiple databases. Schema evolution of one database may invalidate spatial views in its database or even other databases.

This research focuses on managing evolution in a federated spatial database system and spatial view environment. The aim of the research is to develop an effective approach and tools to manage schema evolution in a federated spatial database system in order to overcome mismatch between evolved schema and users’ spatial views. An in-depth study and analysis of schema evolution will be conducted and a rich, complex set of schema changes will be presented. Schema evolution propagation and spatial views adaptation algorithms will be developed.